0.Description initial dataset

0.1 Data loading schema

0.2 Data description

Task 1: "Analyze vehicle speed"

1.1 Task pipeline schema

1.2 Pseudo-algorithm schema

1.2 Let's have a look on the data and summary stat.

Table: Data summary

Name dt_hour
Number of rows 1471
Number of columns 5
Key NULL
_______________________
Column type frequency:
character 1
factor 1
numeric 3
________________________
Group variables None

Variable type: character

skim_variable n_missing complete_rate min max empty n_unique whitespace
type_vehicle 0 1 1 1 0 3 0

Variable type: factor

skim_variable n_missing complete_rate ordered n_unique top_counts
line_id 0 1 FALSE 73 6: 23, 3: 22, 5: 22, 7: 22

Variable type: numeric

skim_variable n_missing complete_rate mean sd p0 p25 p50 p75 p100 hist
hour 0 1 12.88 6.31 0.00 8.00 13.00 18.00 23.00 ▃▇▆▇▇
avg_speed_hour 0 1 23.25 12.34 -0.01 13.91 22.74 31.25 60.27 ▅▇▆▃▁
avg_delay_hour 0 1 347.65 181.75 -1.56 197.87 323.76 479.49 1740.08 ▇▆▁▁▁

1.3 Vizualize hourly average speed by typology

1.4 Visualize plots by moments and typology

Task 2: "Analyze vehicle delays in Seconds."

2.1 Task pipeline schema

2.2 Pseudo-algorithm schema

2.2. Visualization by vehicle type

2.3 Visualization by moments and vehicle

2.4 Testing coordinates map w.r.t to stops

Data coordinates w.r.t to the stops

Plot test single coordinate